MULTI-SENSOR DATA COLLECTION and/or PROCESSING

ABSTRACT

The subject matter disclosed herein relates to the control and utilization of multiple sensors within a device. For an example, motion of a device may be detected in response to receipt of a signal from a first sensor disposed in the device, and a power state of a second sensor also disposed in the device may be changed in response to detected motion.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority to provisional U.S. ApplicationNo. 60/896,795, entitled, “Multi-Sensor Measurement Processing Unit”filed on Mar. 23, 2007, to provisional U.S. Application No. 60/909,380,entitled, “Multi-Sensor Measurement Processing Unit” filed on Mar. 30,2007, and provisional U.S. Application No. 60/914,716, entitled“Multi-Sensor Measurement Processing Unit” filed on Apr. 27, 2007, whichis assigned to the assignee hereof and which is expressly incorporatedherein by reference.

BACKGROUND

1. Field

The subject matter disclosed herein relates to the collection and/orprocessing of sensor data from multiple sensors.

2. Information

A variety of sensors are available to support a number of applicationsin today's market. These sensors may convert physical phenomena intoanalog and/or electrical signals. Such sensors may include, for example,a barometric pressure sensor. A barometric pressure sensor may be usedto measure atmospheric pressure. Applications for the barometricpressure sensor may include determining altitude. Other applications mayinclude observing atmospheric pressure as it relates to weatherconditions.

Another sensor type may include an accelerometer. An accelerometer maysense the direction of gravity and any other force experienced by thesensor. The accelerometer may be used to sense linear and/or angularmovement, and may also be used, for example, to measure tilt and/orroll.

Yet another sensor type may include a gyroscope which measures theCoriolis effect and may be used in applications measuring headingchanges or in measuring rate of rotation. Gyroscopes have, for example,important applications in the field of navigation.

Another type of sensor may include a magnetic field sensor that maymeasure the strength of a magnetic field and, correspondingly, thedirection of a magnetic field. A compass is an example of a magneticfield sensor. The compass may find use in determining absolute headingin car and pedestrian navigation applications.

Biometric sensors represent another type of sensors that may have avariety of possible applications. Some examples of biometric sensors mayinclude heart rate monitors, blood pressure monitors, fingerprintdetection, touch (heptic) sensors, blood sugar (glucose) level measuringsensors, etc.

The above sensors, as well as other possible sensors not listed, may beutilized individually or may be used in combination with other sensors,depending on the particular application. For example, in navigationapplications, accelerometers, gyroscopes, geomagnetic sensors, andpressure sensors may be utilized to provide adequate degrees ofobservability. For one example, the accelerometer and gyroscope mayprovide six axes of observability (x, y, z, τ, φ, ψ). As mentionedabove, the accelerometer may sense linear motion (translation in anyplane, such as a local horizontal plane). This translation may bemeasured with reference to at least one axis. The accelerometer may alsoprovide a measure of an object's tilt (roll or pitch). Thus, with theaccelerometer, an object's motion in Cartesian coordinate space (x, y,z) may be sensed, and the direction of gravity may be sensed to estimatean object's roll and pitch. The gyroscope may be used to measure therate of rotation about (x, y, z), i.e., roll (τ) and pitch (φ) and yaw,which may also be referred to as azimuth or “heading” (ψ).

Navigational applications are merely one example of how more than onesensor type may be utilized in combination to provide multi-axesmeasurement capabilities. The utilization of multiple sensors to performmeasurements may present a number of challenges to users of thesedevices. Such challenges may include, for example, size, cost,interfaces, connectivity, and/or power consumption of the multiplesensors.

SUMMARY

In one aspect, motion of a device may be detected in response to receiptof a signal from a first sensor disposed in the device, and a powerstate of a second sensor also disposed in the device may be changed inresponse to detected motion.

BRIEF DESCRIPTION OF THE FIGURES

Non-limiting and non-exhaustive examples will be described withreference to the following figures, wherein like reference numeralsrefer to like parts throughout the various figures.

FIG. 1 is a block diagram of an example multi-sensor measurementprocessing unit (MSMPU).

FIG. 2 is a flow diagram of an example process for power managing aplurality of sensors integrated within a single device.

FIG. 3 is a block diagram of an additional example of a multi-sensormeasurement processing unit.

FIG. 4 is a flow diagram of an example process for switching operationalmodes of a gyroscope in response to motion detected by an accelerometer.

FIG. 5 is a block diagram of a further example of a multi-sensormeasurement processing unit.

FIG. 6 is a flow diagram of an example process for time-stampingbuffered sensor data.

FIG. 7 is a flow diagram of an example process for calibrating sensors.

FIG. 8 is a flow diagram of an example process for determining whether amobile station has entered or exited a specified region.

FIG. 9 is a flow diagram of an example process for combining acceleratorand gyroscope measurements.

FIG. 10 is a block diagram of an additional example of an MSMPU.

FIG. 11 is a block diagram of an example mobile station incorporating anMSMPU.

DETAILED DESCRIPTION

Reference throughout this specification to “one example”, “one feature”,“an example” or “a feature” means that a particular feature, structure,or characteristic described in connection with the feature and/orexample is included in at least one feature and/or example of claimedsubject matter. Thus, the appearances of the phrase “in one example”,“an example”, “in one feature” or “a feature” in various placesthroughout this specification are not necessarily all referring to thesame feature and/or example. Furthermore, the particular features,structures, or characteristics may be combined in one or more examplesand/or features.

The methodologies described herein may be implemented by various meansdepending upon applications according to particular examples. Forexample, such methodologies may be implemented in hardware, firmware,software, and/or combinations thereof. In a hardware implementation, forexample, a processing unit may be implemented within one or moreapplication specific integrated circuits (ASICs), digital signalprocessors (DSPs), digital signal processing devices (DSPDs),programmable logic devices (PLDs), field programmable gate arrays(FPGAs), processors, controllers, micro-controllers, microprocessors,electronic devices, other devices units designed to perform thefunctions described herein, and/or combinations thereof.

“Instructions” as referred to herein relate to expressions whichrepresent one or more logical operations. For example, instructions maybe “machine-readable” by being interpretable by a machine for executingone or more operations on one or more data objects. However, this ismerely an example of instructions and claimed subject matter is notlimited in this respect. In another example, instructions as referred toherein may relate to encoded commands which are executable by aprocessing circuit having a command set which includes the encodedcommands. Such an instruction may be encoded in the form of a machinelanguage understood by the processing circuit. Again, these are merelyexamples of an instruction and claimed subject matter is not limited inthis respect.

“Storage medium” as referred to herein relates to media capable ofmaintaining expressions which are perceivable by one or more machines.For example, a storage medium may comprise one or more storage devicesfor storing machine-readable instructions and/or information. Suchstorage devices may comprise any one of several media types including,for example, magnetic, optical or semiconductor storage media. Suchstorage devices may also comprise any type of long term, short term,volatile or non-volatile memory devices. However, these are merelyexamples of a storage medium, and claimed subject matter is not limitedin these respects.

Unless specifically stated otherwise, as apparent from the followingdiscussion, it is appreciated that throughout this specificationdiscussions utilizing terms such as “processing,” “computing,”“calculating,” “selecting,” “forming,” “enabling,” “inhibiting,”“locating,” “terminating,” “identifying,” “initiating,” “detecting,”“obtaining,” “hosting,” “maintaining,” “representing,” “estimating,”“receiving,” “transmitting,” “determining” and/or the like refer to theactions and/or processes that may be performed by a computing platform,such as a computer or a similar electronic computing device, thatmanipulates and/or transforms data represented as physical electronicand/or magnetic quantities and/or other physical quantities within thecomputing platform's processors, memories, registers, and/or otherinformation storage, transmission, reception and/or display devices.Such actions and/or processes may be executed by a computing platformunder the control of machine-readable instructions stored in a storagemedium, for example. Such machine-readable instructions may comprise,for example, software or firmware stored in a storage medium included aspart of a computing platform (e.g., included as part of a processingcircuit or external to such a processing circuit). Further, unlessspecifically stated otherwise, processes described herein, withreference to flow diagrams or otherwise, may also be executed and/orcontrolled, in whole or in part, by such a computing platform.

Wireless communication techniques described herein may be in connectionwith various wireless communication networks such as a wireless widearea network (WWAN), a wireless local area network (WLAN), a wirelesspersonal area network (WPAN), and so on. The term “network” and “system”may be used interchangeably herein. A WWAN may be a Code DivisionMultiple Access (CDMA) network, a Time Division Multiple Access (TDMA)network, a Frequency Division Multiple Access (FDMA) network, anOrthogonal Frequency Division Multiple Access (OFDMA) network, aSingle-Carrier Frequency Division Multiple Access (SC-FDMA) network, orany combination of the above networks, and so on. A CDMA network mayimplement one or more radio access technologies (RATs) such as cdma2000,Wideband-CDMA (W-CDMA), to name just a few radio technologies. Here,cdma2000 may include technologies implemented according to IS-95,IS-2000, and IS-856 standards. A TDMA network may implement GlobalSystem for Mobile Communications (GSM), Digital Advanced Mobile PhoneSystem (D-AM PS), or some other RAT. GSM and W-CDMA are described indocuments from a consortium named “3rd Generation Partnership Project”(3GPP). Cdma2000 is described in documents from a consortium named “3rdGeneration Partnership Project 2” (3GPP2). 3GPP and 3GPP2 documents arepublicly available. A WLAN may comprise an IEEE 802.11x network, and aWPAN may comprise a Bluetooth network, an IEEE 802.15x, for example.Wireless communication implementations described herein may also be usedin connection with any combination of WWAN, WLAN and/or WPAN.

In one example, a device and/or system may estimate its location based,at least in part, on signals received from satellites. In particular,such a device and/or system may obtain “pseudorange” measurementscomprising approximations of distances between associated satellites anda navigation satellite receiver. In a particular example, such apseudorange may be determined at a receiver that is capable ofprocessing signals from one or more satellites as part of a SatellitePositioning System (SPS). Such an SPS may comprise, for example, aGlobal Positioning System (GPS), Galileo, Glonass, to name a few, or anySPS developed in the future. To determine its position, a satellitenavigation receiver may obtain pseudorange measurements to three or moresatellites as well as their positions at time of transmitting. Knowingthe satellite's orbital parameters, these satellite positions can becalculated for any point in time. A pseudorange measurement may then bedetermined based, at least in part, on the time a signal travels from asatellite to the receiver, multiplied by the speed of light. Whiletechniques described herein may be provided as implementations oflocation determination in a GPS, EGNOS, WAAS, Glonass and/or Galileotypes of SPS as specific illustrations, it should be understood thatthese techniques may also apply to other types of SPS, and that claimedsubject matter is not limited in this respect.

Techniques described herein may be used with any one or more of severalSPS, including the aforementioned SPS, for example. Furthermore, suchtechniques may be used with positioning determination systems thatutilize pseudolites or a combination of satellites and pseudolites.Pseudolites may comprise ground-based transmitters that broadcast a PRNcode or other ranging code (e.g., similar to a GPS or CDMA cellularsignal) modulated on an L-band (or other frequency) carrier signal,which may be synchronized with GPS time. Such a transmitter may beassigned a unique PRN code so as to permit identification by a remotereceiver. Pseudolites may be useful in situations where SPS signals froman orbiting satellite might be unavailable, such as in tunnels, mines,buildings, urban canyons or other enclosed areas. Another implementationof pseudolites is known as radio-beacons. The term “satellite”, as usedherein, is intended to include pseudolites, equivalents of pseudolites,and possibly others. The term “SPS signals”, as used herein, is intendedto include SPS-like signals from pseudolites or equivalents ofpseudolites.

As used herein, mobile station (MS) refers to a device that may fromtime to time have a position or location that changes. The changes inposition and/or location may comprise changes to direction, distance,orientation, etc., as a few examples. In particular examples, a mobilestation may comprise a cellular telephone, wireless communicationdevice, user equipment, laptop computer, personal navigation device(PND), personal multimedia player (PMP), other personal communicationsystem (PCS) device, and/or other portable communication device. Amobile station may also comprise a processor and/or computing platformadapted to perform functions controlled by machine-readableinstructions.

As discussed above, the utilization of multiple sensors to performmeasurements may present a number of challenges to users of thesedevices. Such challenges may include, for example, size, cost,interfaces, connectivity, and/or power consumption of the multiplesensors. In order to address these issues, techniques described hereinmay include integrating two or more sensors in a single device. Such adevice may comprise a component in a mobile station, for example.

Techniques described herein may implement a multi-sensor measurementprocessing unit (MSMPU) to support a wide range of applications such asthose mentioned above, for example, although the scope of claimedsubject matter is not limited to those particular applications. TheMSMPU, in one aspect, may support these applications by providingdesirable signal amplification, conditioning, measurement collection,measurement pre-processing, power management of internal and/or externalcomponents (including externally connected or accessible sensors),and/or communication of raw and/or pre-processed sensor data to anexternal processor. The external processor may comprise, for example, amobile station (MS) modem or any other processor.

FIG. 1 is a block diagram of an example MSMPU 100 coupled to an MS modem(MSM) 110, which may comprise a processor. For this example, MSMPU 100includes a pair of sensors, 130 and 140. Also included in this exampleis a local processor 120. Sensor 130 and/or sensor 140 may comprise anyof a wide range of sensor types, including, but not limited to,accelerometers, gyroscopes, geomagnetic, pressure, biometric, andtemperature sensors, etc. In one aspect, local processor 120 maycomprise a power management system comprising, for example, circuitryand/or may execute a power management program. Sensors 130 and 140 maytransition between power stages under control of the power managementsystem in order to selectively control power consumption in one or bothsensors. For example, sensor 130 may be placed in an “off” or “sleepmode” state where the sensor is drawing little or no power. Sensor 140may operate in a low power mode, perhaps with limited functionality.Sensor 140 may at some point detect a trigger event. If sensor 140detects a trigger event, local processor 120 may turn on sensor 130, andmay also place sensor 140 in a normal operating mode. Alternatively, inanother aspect, sensor 140 may operate in a normal mode while sensor 130may be placed in an “off” or “low power mode” state. If sensor 140detects a trigger event, local processor 120 may turn on sensor 130 andplace it in a normal operating mode as well.

In one aspect, the power management system may comprise dedicated logicin local processor 120. Dedicated logic may manage power on/off, reducedpower operation, and/or sleep modes for various internal and/or externalcomponents. For example, dedicated logic may provide power managementfor sensors 130 and 140. In another aspect, the power management systemmay be implemented at least in part as software instructions that areexecutable on local processor 120.

FIG. 2 is a flow diagram of an example process for power managing a pairof sensors situated within a mobile station. At block 210, a firstsensor is in a sleep mode or “off” mode, meaning that the first sensoris drawing little or no power. Also at block 210, a second sensor isoperating in a low-power mode. At block 220, a determination may be madeas to whether the second sensor has detected a trigger event. Inresponse to the second sensor detecting a trigger event, at block 230the first sensor may be placed into a normal operational mode and thesecond sensor may also be placed into a normal operational mode in orderto perform a measurement activity. The two sensors may stay in thenormal operational modes until the measurement activity is completed. Atblock 240, if the measurement activity is completed, the first sensormay be turned off or put in a “sleep” mode while the second sensor isplaced into the low-power mode at block 210. Examples in accordance withclaimed subject matter may include all, more than all, or less than allof blocks 210-240. Further, the flow diagram of FIG. 2 is merely anexample technique for power managing a pair of sensors, and claimedsubject matter is not limited in this respect.

FIG. 3 is a block diagram of an example MSMPU 300 comprising a localprocessor 320, a memory 360, a power management unit 350, a gyroscope330, and accelerometer 340, and a temperature sensor 335. MSMPU 300 maybe coupled to an external processor, such as, for example, MSM 310. Forthis example, gyroscope 330 and/or accelerometer 340 may provide analogsignals to local processor 320. MSMPU may comprise an analog-to-digitalconverter (A/D) 305 for digitizing analog signals from gyroscope 330,accelerometer 340, and/or other sensors. For this example, a geomagneticsensor 370 and a barometric pressure sensor 380 are coupled to MSMPU300. In one aspect, signal amplification and conditioning circuitry maybe included to process externally connected analog sensors such asgeomagnetic sensor 370. Although example MSMPU 300 is described with A/D305 and memory 360 as being integrated within local processor 320, otherexamples are possible with one or both of A/D 305 and memory 360 notintegrated within local processor 320. Further, the particulararrangement and configuration of MSMPU 300 is merely an example, and thescope of claimed subject matter is not limited in these respects.

For this example, geomagnetic sensor 370 is not integrated into MSMPU300, but is disposed elsewhere within the device incorporating MSMPU300. The ability to position the geomagnetic sensor separately fromMSMPU may allow for flexible placement of the geomagnetic sensor.Accordingly, such flexibility in placement of a geomagnetic sensor mayenable greater flexibility in form factor design and placement to reducethe effects of electromagnetic interference and/or temperature, forexample.

In one aspect, external sensors 370 and/or 380 as well as MSM 310 may becoupled to MSMPU 300 via any of a wide range of interconnect types,including, but not limited to, I2C and/or SPI interconnects. Of course,this is merely an example interconnect type, and the scope of claimedsubject matter is not limited in this respect.

In another aspect, MSMPU 300 may implement an interrupt pin coupled toMSM 310 or another component. MSMPU 300 may operate the interrupt signalin a latched interrupt mode, for one example. Further, MSMPU 300 mayincorporate an internal programmable threshold and dedicated circuitryto set the interrupt pin. However, these are merely examples of howinterrupt signaling may be implemented, and the scope of claimed subjectmatter is not limited in this respect.

In another aspect, MSMPU 300 may implement at least one generalprogrammable IO pin (GPIO) coupled to MSM 310 or another component.MSMPU 300 may operate the GPIO pin to power on and off a connectedcomponent, for one example.

In another aspect, power management unit 350 may provide power controlsignals to gyroscope 330 and accelerometer 340. Power management unit350 may be implemented as dedicated circuitry, or may be implemented assoftware and/or firmware stored in memory 360 and executed by localprocessor 320.

For one example, gyroscope 330 may be turned off while accelerometer 340is operating in a low power mode. Accelerometer 340 may operate while inthe low power mode to detect motion of the device incorporating theMSMPU 300. If motion is detected, accelerometer 340 may be put into anormal operational mode and gyroscope 330 may also be powered on and putinto a normal operational mode. In one aspect, each of the sensors 330and 340, as well as for some implementations external sensors such asgeomagnetic sensor 370 and barometric sensor 380, may be powered on, putto sleep, put into low power operational modes, and/or put into normaloperational modes independently of one another. In this manner, powermanagement unit 350 may tailor power consumption across a wide range ofpossible applications, situations, and performance requirements. Inanother aspect, MSMPU 300 may implement a fast procedure to restorepower for gyroscope 330 and/or accelerometer 340. In one example, one oftwo or more fast procedures to restore power (wake up modes) may beselected, wherein the different modes represent various compromisesbetween wake up time and current consumption.

For an example, the output of accelerometer 340 may be used as a switchto turn on other sensors integrated within MSMPU 300 or elsewhere withinthe device incorporating MSMPU 300. Such external sensors may beincorporated on the same die as MSMPU 300 or may be implemented as asingle system-in-package (SIP). External sensors may also be situatedoutside of the device incorporating MSMPU 300, perhaps remotelyconnected with MSMPU 300 via a wireless interconnect, as describedfurther below, or via another type of interconnect.

In another aspect, sensors integrated within MSMPU 300 may haveprogrammable and/or selectable characteristics. For example,accelerometer 340 may implement a selectable “g” level, perhaps with arange of from 2 to 16 g, in one example. For another example, gyroscope330 may have a selectable angular velocity range, perhaps ranging from50 to 500 deg/sec for one example. However, these are merely exampleranges for accelerometer 340 and gyroscope 330, and the scope of claimedsubject matter is not limited in these respects.

In a further aspect, MSMPU 300 may incorporate a selectable outputresolution for measurement data. In one example, resolutions of eitherseven bits for low power consumption modes or fourteen to sixteen bitsfor normal operational modes may be selected. Also, MSMPU may operate ata selectable bandwidth for the interface to MSM 310. For one example,the bandwidth may be selectable between 25 and 1500 Hz.

In another aspect, MSMPU 300 and its associated sensors may be used innavigational applications. Accelerometer 340 may be pre-programmedand/or preconfigured to detect the movement (change in acceleration)and/or change in the tilt angle of the device incorporating MSMPU 300 aseither exceeding, falling below, or being between two thresholds (upperand lower) to trigger power management functions for one or more of theother sensors. In this manner, for this example, geomagnetic sensor 370and/or gyroscope 330 and/or barometric pressure sensor 380 and/or acamera sensor (not shown) and/or any other sensor integrated into thedevice incorporating the MSMPU or remotely connected to the MSMPU can bepowered on if motion is detected in order to perform the navigationapplication. Similarly, if motion is not detected (the device isstationary), the accelerometer output may be used to put any or all theother sensors in a sleep, low power, or off mode, thus reducing thepower consumption.

FIG. 4 is a flow diagram of an example process for power managing two ormore sensors including an accelerometer within a mobile station. Atblock 410, one or more sensors are in a sleep mode, meaning that the oneor more sensors are drawing little or no power. Also at block 410, anaccelerometer may operate in a low-power mode. Block 420 indicates thatif the accelerometer detects movement, at block 430 the one or moresensors previously put in sleep mode may be wakened to operate in anormal operational mode. The accelerometer may also be put into a normaloperational mode in order to perform a measurement activity inconjunction with the one or more other sensors, perhaps including agyroscope and/or a geomagnetic sensor. The various sensors may stay inthe normal operational modes until the measurement activity, perhapsincluding navigational operations for one example, is completed. Atblock 440, if the measurement activity is completed, the one or moresensors may be returned to sleep mode and the accelerometer may beplaced into the low-power mode at block 410. Examples in accordance withclaimed subject matter may include all, more than all, or less than allof blocks 410-440. Further, the flow diagram of FIG. 4 is merely anexample technique, and claimed subject matter is not limited in thisrespect.

In another aspect, accelerometer 340 may be used to detect a free-fallcondition of the device incorporating the MSMPU, perhaps a mobilestation, in order to power down gyroscope 330 to protect the gyroscopefrom damage upon impact. This process may be analogous to a process ofparking a read/write head of a hard disk to protect it from impact of afall.

As previously described, the power control logic implemented withinMSMPU 300 may power on or off or switch the operational modes of notonly the internal sensors such as accelerometer 340 and gyroscope 330,but may also power on or off or switch the operational modes of externalsensors such as geomagnetic sensor 370 and barometric pressure sensor380. In another aspect, power management unit 350 may also be adapted topower on or off or switch the operational modes of an externalprocessor, such as, for one example, MSM 310. In a further aspect, powermanagement unit 350 may execute processes to determine conditions underwhich it may be advantageous to switch modes of operation for variousinternal and external sensors and/or processors and/or other components.Of course, these are merely examples of power management processes thatmay be executed by power management unit 350, and the scope of claimedsubject matter is not limited in this respect.

In another example, local processor 320 may be used to detect motionbased on the measurements from at least one of accelerometer 340 andgyroscope 330. Furthermore, the motion detection event may be used tostart the execution of the instructions resident on an externalprocessor such as MSM 310.

FIG. 5 is a block diagram of an example MSMPU 500 coupled to a mobilestation modem (MSM) 510. MSMPU 500 and MSM 510 may, for one example, beincorporated into a mobile station. MSMPU 500 may comprise a localprocessor 520, a memory 560, a power management unit 550, a gyroscope530, an accelerometer 540, and a temperature sensor 535. For oneexample, gyroscope 530 and/or accelerometer 540 may provide analogsignals to local processor 520. MSMPU may comprise an analog-to-digitalconverter (A/D) 505 for converting analog signals from gyroscope 530,accelerometer 540, and/or other sensors. In an aspect, power managementunit 550 may provide power control signals to gyroscope 530 andaccelerometer 540. Power management unit 550 may be implemented asdedicated circuitry, or may be implemented as software and/or firmwarestored in memory 560 and executed by local processor 520. For thisexample, MSMPU 500 may further be coupled to a barometric pressuresensor 580 and a geomagnetic sensor 570, and may also receive a wheeltick/odometer signal 585 and an external clock signal 587. However, thisis merely one example configuration of an MSMPU and associated sensorsand signals, and the scope of claimed subject matter is not limited inthis respect.

Also for this example, MSMPU may comprise one or more buffers adapted tostore data from sensors, and/or from local processor 520, and/or from anexternal processor such as MSM 510. For the example depicted in FIG. 5,MSMPU 500 may comprise a raw data buffer 522 and a processed data buffer524. The buffering capability provided by buffers 522 and/or 524 may beused for various measurements being generated by various componentsincluded in and/or coupled to MSMPU 500. For example, a rate at whichmeasurements may be obtained from one or more sensors may be differentfrom a rate at which these measurements are either processed in by thelocal processor 520 and/or transmitted to an external component such asan external processor, perhaps MSM 510 in one example. Further,measurement data from one or more sensors may be collected in one ormore buffer in order to transmit the data to MSM 510 or other componentin a burst fashion. In another aspect, raw data buffer 522 may be usedto store data in its raw form (as delivered by one or more sensors) andthe processed data buffer may be used for data that may have beenprocessed in some fashion either by local processor 520 or by anexternal processor such as MSM 510. Such processing may include any typeof filtering, averaging, sub-sampling, outlier detection, and/or timestamping the data to associate an instance of time with one or moremeasurements. Of course, the buffering techniques described herein aremerely example techniques, and the scope of claimed subject matter isnot limited in this respect.

Yet another aspect may comprise the time stamping of various sensormeasurements upon storing the measurements in a buffer, such as, forexample, either buffer 522 or buffer 524, or upon storing themeasurements in a memory, such as, for example, memory 560. Measurementdata may also be time-stamped upon transmitting the measurement data toan external component, such as, for example, MSM 510. The time stampingmay be based, in an example, upon a clock signal received over externalclock signal 587. For an example, external clock signal 587 may begenerated by any of various common crystals, for example a 32 KHzcrystal. The external clock signal may also be used by localphase-locked loop (PLL) circuitry to synthesize the higher frequencysignal needed to run the local processor.

In another aspect, a periodic time reference pulse, perhaps one pulseper second for one example, may be accepted by MSMSPU 500 from MSM 510or other external processor which has access to a reference timestandard such as that provided by an SPS, or by the CoordinatedUniversal Time (UTC) standard, or by any other well known system time.Buffer data may be time-stamped with information derived from suchsystem time information, for example time information derived from anSPS. In this manner, time stamps may be synchronized to a reference timethat may enable a combination of sensor data with other time-stampeddata, such as SPS satellite measurements for navigation applications. Inanother aspect, an external processor (for example, a client for sensorinformation) may provide timing information such as start and stop timesto define a measurement period for the sensor data. In a navigationapplication these start and stop times may correspond to sequential SPSmeasurement time tags and may be used to synchronize the sensor data tothe received SPS data. Using SPS time tags to define a measurementperiod is merely one example technique, and time tags from a number ofdifferent sources may be used to define measurement time periods inother examples.

FIG. 6 is a flow diagram of an example process for time-stampingmeasurement data. At block 610, measurement data from one or moresensors may be stored in a buffer within a mobile station, wherein themobile station comprises the one or more sensors. At block 620, thestored measurement data may be time-stamped with time informationderived from a satellite positioning system or any other commonreference system. Examples in accordance with claimed subject matter mayinclude all, more than all, or less than all of blocks 610-620. Further,the flow diagram of FIG. 6 merely illustrates an example technique, andclaimed subject matter is not limited in this respect.

In another aspect, a periodic time reference pulse signal such as thatreceived via external clock 587 or via an SPS or other time pulse sourcemay be used to initiate a transmission of sensor data from buffers 522and/or 524 or from memory 560 to an external component such as MSM 510.For example, MSMPU 500 may process sensor measurements according todesired processes, store the sensor data either in one or both ofbuffers 522 and 524 or in memory 560, and then transmit the sensor datain response to receiving the periodic time reference signal or inresponse to receiving a “ready to receive” message from an externalcomponent, such as, for example, MSM 510 or from a device incommunication with MSM 510.

In another example, initiation to transmit may be triggered by a receiptof a “ready to receive” message over any common I/O peripheral orinterface such as I2C, SPI, UART, parallel port, etc. Same peripheralsand/or interfaces may be used to provide the external timing informationto MSMPU 500 for measurement time stamping and/or maintenance of thesynchronization between MSMPU 500 and external component such as MSM510.

In another aspect, circuitry and/or software may be provided tocalibrate sensors either integrated within MSMPU 500 and/or externallyconnected to MSMPU 500. If an external processor such as MSM 510 is usedto execute a navigation application, the navigation application mayestimate one or more states associated with an object such as a mobilestation. The one or more states may include, but are not limited to,geographic location, altitude, speed, heading, orientation, and/or thelike. The one or more estimated states may provide information that maybe used to calibrate various parameters of sensors incorporated withinthe mobile station. Examples of such parameters may includeaccelerometer bias, drift, bias as a function of temperature, drift as afunction of temperature, measurement noise as a function of temperature,sensitivity as a function of temperature, variation in any of theparameters as a result sensor installation (mounting) on the board oraging, etc. However, these are merely examples of parameters that may becalibrated, and the scope of claimed subject matter is not limited inthis respect.

FIG. 7 is a flow diagram of an example process for calibrating a sensor.At 710, a change in at least one of position, velocity and altitude fora mobile station may be measured using one or more sensors integratedinto the mobile station. The change in position may be measured, for anexample, measuring a direction and/or distance traveled for the mobilestation. A change in position for the mobile station may be measuredusing information from a satellite positioning system at 720. At 730, anerror value may be calculated wherein the error value represents adifference between the measurements obtained by the one or more sensorsand the measurements obtained via the satellite positioning system. At740, the one or more sensors may be calibrated based at least in part onthe error value. Examples in accordance with claimed subject matter mayinclude all, more than all, or less than all of blocks 710-740. Further,the flow diagram of FIG. 7 merely illustrates an example technique forcalibrating a sensor, and claimed subject matter is not limited in thisrespect.

In another aspect, circuitry and/or software and/or firmware may beprovided to allow a determination that the device incorporating MSMPU500 is stationary. The determination may be performed by software and/orfirmware executed on local processor 520 or may be provided via anexternal input. For example, a wheel tick/odometer input signal 585 mayindicate a stationary condition. In one aspect, wheel tick/odometerinput signal 585 may be used in performing sensor calibration processes.In another aspect, the stationary condition may be used to calibrategyroscope 530 and/or barometric pressure sensor 580. If the deviceincorporating MSMPU 500 is known to be stationary, any change inpressure can be attributed to the actual variation in pressure and notto a change in altitude.

In a further aspect, MSMPU may be incorporated into any of a range ofdevices, including, for example, cell phones, personal digitalassistants, notebook computers, etc. Such devices may on occasion beplaced into a cradle or docking station. In one example, when such adevice is placed in the cradle or docking station, the device isstationary. MSMPU 500 may sense or may receive an indication that such adevice is placed in the cradle or docking station, deducing that thedevice is stationary. In an example, the indication of a stationarycondition may be utilized in performing calibration operations such asdiscussed above. In another aspect, MSMPU 500 may detect the transitionout of a stationary condition, for example through motion detection.

In an additional aspect, temperature sensor 535 may provide temperaturemeasurements that may be used in performing calibration operations inorder to develop sensor performance characteristics as a function oftemperature. In one example, a table of accelerometer drift values as afunction of temperature may be learned and stored in memory 560. Thesensor calibration data (such as bias and drift) may be provided toMSMPU 500 for sensor data correction. Correcting raw sensor data withcalibration data may provide capabilities for various applications,including, but not limited to, motion detection and motion integrationfor dead-reckoning application. Dead reckoning (DR) may refer to aprocess of estimating one's current position and advancing that positionbased on known or measured speed, elapsed time, and heading.

In another aspect, data from geometric sensor 570 may be used tocalibrate gyroscope 530 biases and may also be used to initialize anabsolute heading indicated by the geomagnetic sensor. In order toprovide better directional information, it may be advantageous forgeomagnetic sensor 570 to be tilt-compensated using roll and pitchmeasurements from accelerometer 540. Tilt-compensation processes may beimplemented by dedicated circuitry resident on MSMPU 500 and/or may beimplemented in software and/or firmware that may be executed by localprocessor 520 and/or MSMPU 500. The tilt-compensation processes mayutilize measurement data received from externally connected geomagneticsensor 570. It may also be advantageous to incorporate data fromtemperature sensor 535 or from another temperature sensor eitherintegrated into geomagnetic sensor 570 or placed in close proximity togeomagnetic sensor 570. In another aspect, gyroscope 530 may becalibrated using sequential and/or periodic and/or event-triggeredmeasurements from geomagnetic sensor 570 to measure the change in theangular information.

In yet another aspect, MSMPU 500 may perform motion integration byincorporating measurements from accelerometer 540 and gyroscope 530 todetermine the change in the distance and direction traveled (e.g.,trajectory or path of motion). This aspect may be advantageouslyemployed in geo-fencing applications where it is desirable to determineif an object incorporating MSMPU 500 has exited or entered an area ofinterest. The area of interest may be defined as a circle with a presetand/or programmable radius, for an example, although this is merely anexample of how an area of interest may be defined, and the scope ofclaimed subject matter is not limited in this respect.

FIG. 8 is a flow diagram illustrating an example geo-fence application.At block 810, a starting position may be established for a mobilestation. At block 820, a change in position for the mobile station maybe detected using accelerometer and gyroscope sensor data. The change inposition may be detected, in an example, by detecting a direction and/ordistance traveled for the mobile station using techniques known to thoseof ordinary skill in the art. At block 830, a determination may be madeas to whether the mobile station has exited or entered a specifiedregion. Examples in accordance with claimed subject matter may includeall, more than all, or less than all of blocks 810-830. Further, theflow diagram of FIG. 8 merely illustrates an example technique forgeo-fencing, and claimed subject matter is not limited in this respect.

FIG. 9 is a flow diagram of an example process for combining informationfrom both accelerometer 540 and gyroscope 530. Such information maycomprise motion integration and rotation data, and such information maybe utilized to support geo-fencing and/or navigation DR operations. Ingeneral, information from gyroscope 530 may be used to compute how muchthe mobile station's orientation has been rotated from the originalorientation, in three dimensional space. The resulting rotation matrixmay be used to convert the accelerometer information back to themeasurement frame (orientation) that the accelerometer was in at thebeginning of the measurement period. These “rotated” measurements may beadded to previous measurements to determine a net displacement, becausethe measurements are all based on the same orientation. In particular,for this example technique, at block 905, data may be acquired from agyroscope, such as, for example gyroscope 530. At block 910, 3×3matrices may be created, and at block 925 individual roll, pitch, andyaw (heading) values may be summed. The matrices from block 910 may bemultiplied at block 915 to accumulate the rotations. A matrix multipliedwith the first rotation matrix may be identified. At block 920, thematrix may be inverted to rotate the sample back to the start of theinterval. Processing may proceed to block 940. At block 930,accelerometer data (x, y, z) may be acquired, and at block 935 a 3×1vector may be created. At block 940, the inverted matrix from block 920may be used to rotate the sample point back to the starting point. Atblock 945, individual frames from within the same reference frame may besummed. At block 950, the accumulated rotations (from gyroscopemeasurements) and distance traveled (from accelerometer measurements)may be combined. Examples in accordance with claimed subject matter mayinclude all, more than all, or less than all of blocks 905-950. Further,the flow diagram of FIG. 9 merely illustrates an example technique forcombining accelerator and gyroscope measurements, and claimed subjectmatter is not limited in this respect.

FIG. 10 is a block diagram of an example MSMPU 1000 comprising wirelessconnectivity. MSMPU may comprise similar technologies as described abovein connection with FIGS. 3 and 5. Wireless connectivity may beaccomplished via any of a wide range of wireless technologies, includingfuture technologies. Bluetooth, ZigBee, Near Field Communication (NFC),WiFi, and Ultra Wide Band (UWB) are just a few examples of such wirelesstechnologies, and the scope of claimed subject matter is not limited inthis respect. These technologies are represented in FIG. 10 by wirelesscommunication units 1092, 1094, 1096, and 1098. By adding wirelessconnectivity, a device integrating MSMPU 1000 may be able to communicatewith another device which also includes an MSMPU 1084 for peer-to-peerapplications such as multi-player games, as one example. MSMPU 1000 mayalso communicate with an external processor 1082 to provide processor1082 with raw sensor measurements, processed sensor measurements,positional (x,y,z) and/or attitude information (τ,φ,ψ) in any number ofdegrees (depending on the availability and operational status ofintegrated or connected sensors), change in positional and/or attitudeinformation, Euler angles, quaternion, telemetry data, etc.

In another aspect, MSMPU 1000 may also communicate through any of thewireless technologies with one or more biometric sensors, such as, forexample, heart rate monitor (HRM) 1086 and/or blood pressure (BP)monitor 1088. Such sensors may find application in medical and/orfitness/athletic fields, for example.

Information gathered from internal and/or external sensors may be usedby external processor 1082 to derive a navigational solution, and/oruser interface and/or gaming control signals, camera image stabilizationsignals, etc. In another example, data from at least one MSMPU may beprovided to a central processing unit to derive a relative positionaland/or attitude information that may be used in a multi-player gamingenvironment where actions or change in position or change in attitude ofone player with respect to another player are desirable to know.

FIG. 11 is a block diagram of an example of a mobile station 1100. Aradio transceiver 1170 may be adapted to modulate an RF carrier signalwith baseband information, such as voice or data, onto an RF carrier,and demodulate a modulated RF carrier to obtain such basebandinformation. An antenna 1172 may be adapted to transmit a modulated RFcarrier over a wireless communications link and receive a modulated RFcarrier over a wireless communications link.

A baseband processor 1160 may be adapted to provide baseband informationfrom a central processing unit (CPU) 1120 to transceiver 1170 fortransmission over a wireless communications link. Here, CPU 1120 mayobtain such baseband information from an input device within a userinterface 1110. Baseband processor 1160 may also be adapted to providebaseband information from transceiver 1170 to CPU 1120 for transmissionthrough an output device within user interface 1110.

User interface 1110 may comprise a plurality of devices for inputting oroutputting user information such as voice or data. Such devices mayinclude, by way of non-limiting examples, a keyboard, a display screen,a microphone, and a speaker.

A receiver 1180 may be adapted to receive and demodulate transmissionsfrom an SPS, and provide demodulated information to correlator 1140.Correlator 1140 may be adapted to derive correlation functions from theinformation provided by receiver 1180. Correlator 1140 may also beadapted to derive pilot-related correlation functions from informationrelating to pilot signals provided by transceiver 1170. This informationmay be used by a mobile station to acquire wireless communicationsservices. Channel decoder 1150 may be adapted to decode channel symbolsreceived from baseband processor 1160 into underlying source bits. Inone example where channel symbols comprise convolutionally encodedsymbols, such a channel decoder may comprise a Viterbi decoder. In asecond example, where channel symbols comprise serial or parallelconcatenations of convolutional codes, channel decoder 1150 may comprisea turbo decoder.

A memory 1130 may be adapted to store machine-readable instructionswhich are executable to perform one or more of processes,implementations, or examples thereof which are described or suggestedherein. CPU 1120 may be adapted to access and execute suchmachine-readable instructions.

Mobile station 1100 for this example comprises an MSMPU 1190. MSMPU 1190may be adapted to perform any or all of the sensor measurement and/orpower management operations described herein. For example, MSMPU 1190may be adapted to perform the functions described above in connectionwith FIGS. 1-10.

While there has been illustrated and described what are presentlyconsidered to be example features, it will be understood by thoseskilled in the art that various other modifications may be made, andequivalents may be substituted, without departing from claimed subjectmatter. Additionally, many modifications may be made to adapt aparticular situation to the teachings of claimed subject matter withoutdeparting from the central concept described herein. Therefore, it isintended that claimed subject matter not be limited to the particularexamples disclosed, but that such claimed subject matter may alsoinclude all aspects falling within the scope of the appended claims, andequivalents thereof.

1. A method, comprising: detecting motion of a device in response toreceipt of a signal from a first sensor disposed in said device; andchanging a power state of a second sensor, also disposed in said device,in response to said detecting said motion.
 2. The method of claim 1,wherein said detecting motion comprises detecting motion of said devicein response to receipt of a signal from an accelerometer disposed insaid device.
 3. The method of claim 1, wherein said changing the powerstate of the second sensor comprises changing the power state of agyroscope disposed in said device in response to said detecting saidmotion.
 4. The method of claim 1, wherein said changing a power state ofthe second sensor comprises changing the power state of the secondsensor from a sleep mode to a normal operational mode.
 5. The method ofclaim 1, wherein said changing a power state of the second sensorcomprises powering down the second sensor.
 6. The method of claim 1,further comprising: changing a power state of the first sensor inresponse to receipt of the signal from the first sensor.
 7. The methodof claim 5, wherein said changing the power state of the first sensorcomprises changing the power state of the first sensor from a low-powermode to a normal operational mode.
 8. A method, comprising: storingmeasurement data from one or more sensors in a buffer within a mobilestation, wherein the mobile station comprises the one or more sensors;and time-stamping the stored measurement data with time informationderived from a satellite positioning system.
 9. The method of claim 8,wherein said time-stamping the stored measurement data comprisestime-stamping the stored measurement data with time information derivedfrom a global positioning system.
 10. The method of claim 8, whereinsaid time-stamping the stored measurement data comprises time-stampingthe stored measurement data with time information derived from a Galileosatellite positioning system.
 11. The method of claim 8, furthercomprising receiving the time information derived from the satellitepositioning system from an external processor.
 12. The method of claim8, further comprising combining the stored measurement data with othertime-stamped data in order to perform a measurement operation.
 13. Themethod of claim 12, wherein said combining the stored measurement datawith other time-stamped data comprises combining the stored measurementdata with time-stamped data from a satellite positioning system in orderto perform a navigational operation.
 14. A method, comprising:establishing a starting position for a mobile station; detecting achange in position of the mobile station with respect to said startingposition using sensor data from an accelerometer and/or a gyroscope,said accelerometer and/or gyroscope being disposed in the mobilestation; and determining whether the mobile station has exited orentered a specified region based, at least in part, on said detectedchange.
 15. The method of claim 14, wherein said detecting a change inposition of the mobile station comprises detecting a direction and adistance traveled for the mobile station.
 16. The method of claim 14,wherein the specified region is defined as a circle with a specifiedradius.
 17. The method of claim 16, wherein the specified radiuscomprises a programmable value.
 18. A mobile station, comprising: anaccelerometer integrated into a multi-sensor measurement processor unit;a geomagnetic sensor positioned externally to the multi-sensormeasurement processor unit and coupled to the multi-sensor measurementprocessor unit, wherein the multi-sensor processor unit is adapted todetect motion based, at least in part, on sensor data from theaccelerometer and the geomagnetic sensor.
 19. The mobile station ofclaim 18, wherein the multi-sensor processing unit is further adapted tocompensate said geomagnetic sensor based, at least in part, on sensordata from the accelerometer.
 20. The mobile station of claim 19, whereinthe sensor data from the accelerometer comprises roll and pitchmeasurement data.
 21. The mobile station of claim 20, further comprisinga gyroscope coupled to the multi-sensor measurement processing unit,wherein the multi-sensor measurement processing unit is further adaptedto calibrate the gyroscope based, at least in part, on measurement datafrom the geomagnetic sensor.
 22. A method, comprising: measuring changein position of a mobile station using one or more sensors integratedinto the mobile station; measuring change in position of the mobilestation using information from a satellite positioning system;calculating an error value representing a difference between themeasurements obtained by the one or more sensors and the measurementsobtained using the satellite positioning system; and calibrating the oneor more sensors based at least in part on the error value.
 23. Themethod of claim 22, wherein said measuring change in position using oneor more sensors comprises measuring a direction and/or distance traveledby said mobile station.
 24. The method of claim 22, wherein saidmeasuring change in position using information from the satellitepositioning system comprises measuring direction and/or distancetraveled by said mobile station.
 25. The method of claim 22, whereinsaid information from the satellite positioning system comprisesinformation from a global positioning system.
 26. The method of claim22, wherein said information from the satellite positioning systemcomprises information from a Galileo satellite positioning system.
 27. Amulti-sensor measurement processing unit, comprising: a processor; oneor more sensors coupled to the processor; and a wireless interface unitcoupled to the processor, wherein the wireless interface unit is adaptedto receive measurement information from an external sensor via awireless interconnect and wherein said processor is further adapted toestimate one or more navigational states based on said measurementinformation.
 28. The multi-sensor measurement processing unit of claim27, wherein the wireless interface unit is adapted to receivemeasurement information from an external biomedical sensor.
 29. Themulti-sensor measurement processing unit of claim 28, wherein thebiomedical sensor comprises a heart rate monitor.
 30. The multi-sensormeasurement processing unit of claim 28, wherein the biomedical sensorcomprises a blood pressure monitor.
 31. The multi-sensor measurementprocessing unit of claim 27, wherein the wireless interconnect comprisesan interconnect implemented substantially according to a Bluetoothstandard.
 32. The multi-sensor measurement processing unit of claim 27,wherein the wireless interconnect comprises an interconnect implementedsubstantially according to a near field communication standard.
 33. Themulti-sensor measurement processing unit of claim 27, wherein thewireless interface unit is adapted to receive measurement informationfrom an external processor.